Depth Examination of Deep Learning Applications in Crowd Analysis - Elatrash, Eman Mohamed; Esmail, Hanan Mohammed; Infeesh, Salma Ali Alajeli; Khalifa, Zayed Alarabi; Zaqout, Nashwa E. (Journal of Information Systems Research and Practice, 2024)
Artificial neural networks and machine learning have a long history of tackling diverse problems. However, as problems grew in complexity and datasets expanded, computational demands increased significantly. This paper provides a concise overview of the evolution from artificial neural networks to deep learning, highlighting models, applications, and essential technical details, including hardware, software, and libraries. It particularly focuses on conventional methods employed in crowd analysis and delves deeply into the applications of deep learning in this field, accompanied by an examination of relevant datasets. Additionally, recent studies in crowd analysis are meticulously analyzed and compared. In conclusion, crowd analysis stands as both an academic pursuit and a practical domain where deep learning has led to remarkable achievements.